{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.arange(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "b?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.reshape?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.reshape??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello Jupyter\n"
     ]
    }
   ],
   "source": [
    "%run test.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.1 µs ± 173 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.arange(100).reshape(10, 10) * np.arange(100).reshape(10, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "%xdel b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "%magic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x10d6d450>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a = np.random.normal(size=(32, 32))\n",
    "plt.imshow(a)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x126a3430>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.random.randn(1000).cumsum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
